Autonomous structural health monitoring using wireless smart sensors on a cable-stayed bridge

2010 ◽  
pp. 89-89
Author(s):  
S Jang ◽  
H Jo ◽  
K Mechitov ◽  
S Sim ◽  
B Spencer ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Sensors ◽  
Structural Health ◽  
Cable Stayed Bridge ◽  
Wireless Smart Sensors

Wireless structural health monitoring of cable-stayed bridge using Imote2-platformed smart sensors

2012 ◽  
Author(s):  
Duc-Duy Ho ◽  
Khac-Duy Nguyen ◽  
Po-Young Lee ◽  
Dong-Soo Hong ◽  
So-Young Lee ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Sensors ◽  
Structural Health ◽  
Cable Stayed Bridge

Development and full-scale validation of high-fidelity data acquisition on a next-generation wireless smart sensor platform

2019 ◽  
Vol 22 (16) ◽  
pp. 3512-3533 ◽  
Author(s):  
Yuguang Fu ◽  
Kirill Mechitov ◽  
Tu Hoang ◽  
Jong R Kim ◽  
Deuck Hang Lee ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Data Acquisition ◽  
Health Monitoring ◽  
Full Scale ◽  
Smart Sensors ◽  
Smart Sensor ◽  
Structural Health ◽  
Sensor Platforms ◽  
Sensor Platform ◽  
Wireless Smart Sensors

Although wireless smart sensor platforms have been available over a decade, only a limited number of full-scale wireless smart sensor–based structural health monitoring implementations have been realized. Most wireless smart sensor platforms that are validated in full-scale implementations have now become obsolete and are no longer commercially available. While wireless sensing capabilities have grown, presenting significant opportunities, obstacles to wide application of wireless smart sensor for structural health monitoring exist both in terms of hardware and software. This article assesses the efficacy of the Xnode, a new wireless platform whose development has been driven by structural health monitoring requirements, as well as lessons learned from several full-scale wireless smart sensor deployments. The capabilities of the platform are evaluated in comparison with other commercial wireless smart sensors, in terms of hardware, software, and mechanical design. Extensive laboratory and field testing is employed to validate its performance on three aspects: fidelity of data acquisition, reliability of wireless communication, and efficiency of power management. Test results demonstrate the capabilities of the Xnode to support full-scale, high-fidelity data acquisition for civil infrastructure. In addition, the new sensor platform provides several significant benefits to extend the use of wireless smart sensors to a broader class of structural health monitoring applications, such as sudden event monitoring and real-time and control applications.

scholarly journals Prototyping and Validation of MEMS Accelerometers for Structural Health Monitoring—The Case Study of the Pietratagliata Cable-Stayed Bridge

2018 ◽  
Vol 7 (3) ◽  
pp. 30 ◽  
Author(s):  
Chiara Bedon ◽  
Enrico Bergamo ◽  
Matteo Izzi ◽  
Salvatore Noè
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Full Scale ◽  
Shaking Table ◽  
Efficient Design ◽  
Dynamic Identification ◽  
Structural Health ◽  
Cable Stayed Bridge ◽  
Mems Accelerometers

In recent years, thanks to the simple and yet efficient design, Micro Electro-Mechanical Systems (MEMS) accelerometers have proven to offer a suitable solution for Structural Health Monitoring (SHM) in civil engineering applications. Such devices are typically characterised by high portability and durability, as well as limited cost, hence resulting in ideal tools for applications in buildings and infrastructure. In this paper, original self-made MEMS sensor prototypes are presented and validated on the basis of preliminary laboratory tests (shaking table experiments and noise level measurements). Based on the well promising preliminary outcomes, their possible application for the dynamic identification of existing, full-scale structural assemblies is then discussed, giving evidence of their potential via comparative calculations towards past literature results, inclusive of both on-site, Experimental Modal Analysis (EMA) and Finite Element Analytical estimations (FEA). The full-scale experimental validation of MEMS accelerometers, in particular, is performed using, as a case study, the cable-stayed bridge in Pietratagliata (Italy). Dynamic results summarised in the paper demonstrate the high capability of MEMS accelerometers, with evidence of rather stable and reliable predictions, and suggest their feasibility and potential for SHM purposes.

scholarly journals A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

2018 ◽  
Vol 18 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Mehrisadat Makki Alamdari ◽  
Nguyen Lu Dang Khoa ◽  
Yang Wang ◽  
Bijan Samali ◽  
Xinqun Zhu
Keyword(s):  
Data Analysis ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Scale ◽  
Damage Identification ◽  
Tensor Analysis ◽  
Support Vector ◽  
Damage Scenarios ◽  
Structural Health ◽  
Cable Stayed Bridge

A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated; damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold; first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation; second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification; and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities.

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